CN103390249B - Based on the distribution scheduling aid decision method of various dimensions - Google Patents
Based on the distribution scheduling aid decision method of various dimensions Download PDFInfo
- Publication number
- CN103390249B CN103390249B CN201310271161.XA CN201310271161A CN103390249B CN 103390249 B CN103390249 B CN 103390249B CN 201310271161 A CN201310271161 A CN 201310271161A CN 103390249 B CN103390249 B CN 103390249B
- Authority
- CN
- China
- Prior art keywords
- distribution
- load
- management system
- power distribution
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 44
- 230000008569 process Effects 0.000 claims abstract description 17
- 238000013178 mathematical model Methods 0.000 claims abstract description 12
- 230000011218 segmentation Effects 0.000 claims abstract description 12
- 238000004364 calculation method Methods 0.000 claims abstract description 7
- 238000004891 communication Methods 0.000 claims abstract description 6
- 230000003044 adaptive effect Effects 0.000 claims description 12
- 238000012937 correction Methods 0.000 claims description 7
- 230000009977 dual effect Effects 0.000 claims description 5
- 238000007363 ring formation reaction Methods 0.000 claims description 5
- 238000012544 monitoring process Methods 0.000 claims description 4
- 230000005611 electricity Effects 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 3
- 238000002271 resection Methods 0.000 claims description 3
- 230000035772 mutation Effects 0.000 claims description 2
- 238000013461 design Methods 0.000 abstract description 2
- 238000005457 optimization Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 108090000623 proteins and genes Proteins 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000003326 Quality management system Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000010429 evolutionary process Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The present invention relates to a kind of distribution scheduling aid decision method based on various dimensions, its technical characteristics is: comprise the following steps: 1, energy management system, distribution management system and distribution dispatching supplementary decision system terminal are linked together by dispatching communication network; 2, energy management system obtains current power distribution Running State and circuit real time data information; 3, distribution management system adopts self-adaptive threshold segmentation to process power distribution network running status and track data, sets up and turns for mathematical model of load for turning for carry calculation for power distribution network; 4, in distribution dispatching supplementary decision system terminal, the radar map with five dimensions is generated, for yardman provides aid decision making foundation.The present invention is reasonable in design, adopt power distribution network to turn core algorithm for load, realize the real-time online management of power distribution network, efficiently solve existing grid switching operation with problems such as yardman's experience, efficiency are lower, improve stability and the reliability of electrical network, reduce customer outage hours.
Description
Technical field
The invention belongs to distribution network technical field, especially a kind of distribution scheduling aid decision method based on various dimensions.
Background technology
In recent years, along with the development of power grid construction, electric network composition at different levels is significantly strengthened.But urban power distribution network, no matter from grid structure or management level, compares major network still comparatively weak.At present, power distribution network inner city mostly is cable, and network structure adopts ring network structure, and the more suburb of load accounting mostly is overhead transmission line, and network structure has radiant type, simply connected network or many liaison methods.
Present stage scheduling to the management of distribution mainly by the management of drawing data, the data modification drawing reported according to power distribution work area by yardman, not as the energy management system (EMS) of power transmission network, realizing the application of real-time online, is an off-line system departing from scheduling and produce.Because Distributing network structure is complicated, equipment is numerous, measurement data lacks, make to encounter very large difficulty in distribution safety economy scheduling aspect, yardman can only rely on operating experience to process usually, when being not sure, often take the scheme guarded, take open loop operation, power failure operation mode processes.This mode not only fails to make full use of existing Distribution Network Frame structure, give full play to existing distribution once, the effect of secondary device, further increase the power failure probability to user.
In fact, when load and accident treatment (i.e. load transfer plan) are fallen in distribution, often to consider with or without protecting electric task, Operating Complexity (operating switch least number of times), dual power supply number of users, whether can transship (whether branch current can be out-of-limit), can the problem of five aspects such as cyclization (whether busbar voltage can be out-of-limit), as can not be correctly grasped, not only reduce power supply reliability, even can cause very large impact to the stability of electrical network.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of reasonable in design, distribution scheduling aid decision method based on various dimensions that effectively can improve grid stability is provided.
The present invention solves its technical matters and takes following technical scheme to realize:
Based on a distribution scheduling aid decision method for various dimensions, comprise the following steps:
Step 1: energy management system, distribution management system and distribution dispatching supplementary decision system terminal are linked together by dispatching communication network;
Step 2: energy management system is to distribution real time monitoring and carry out data acquisition, obtains current power distribution Running State and circuit real time data information;
Step 3: distribution management system adopts self-adaptive threshold segmentation to process power distribution network running status and track data, sets up and turns for mathematical model of load for turning for carry calculation for power distribution network;
Step 4: when needs carry out grid switching operation, yardman files an application to distribution management system in distribution dispatching supplementary decision system terminal, distribution management system use power distribution network turns and carries out analytical calculation for mathematical model of load, and in distribution dispatching supplementary decision system terminal, generate the radar map with five dimensions, for yardman provides aid decision making foundation.
And described step 3 adopts self-adaptive threshold segmentation to comprise the following steps the detailed process that power distribution network running status and track data process:
(1) mark off target according to the initial information of network and failure message to turn for region, and search for available interconnection switch, determine failure message;
(2) stochastic generation reference group and initial population, and the adaptive value of computing reference individual in population, as reference target;
(3) according to the evolution selected, expand, mutation operation carries out population, for newly-generated individuality, whether this individuality is feasible solution to use basic tree method to judge, if do not meet topological constraints, then uses correction of infeasible solution method to be feasible solution to its reparation.
(4), when finishing iteration process after Evolution of Population to the algebraically set, export after the decoding of the individuality of adaptive value optimum, as final recovery scheme.
And the treatment scheme of described correction of infeasible solution method is: separate P for one for stochastic generation, if be infeasible solution, become feasible solution by repairing; Construct one with reference to population P
re, each individuality in this population is feasible solution; From P
remiddle random selecting one separates r ∈ P
re, then stochastic generation one is from the random number a between 0 to 1, produces the series of points zi be positioned on p and r line segment according to zi=ap+ (1-a) r, until obtain a zi to meet constraint; Now, if the adaptive value of zi is greater than the adaptive value of r, then zi is replaced r, as P
rein one new for individual, thus p is repaired as feasible solution.
And described step 3 power distribution network turns confession mathematical model of load and is:
In above formula, to gain merit resection sum for each load in dead electricity district for the 1st, d
jfor the weight coefficient of a jth load, depend on the kind of load, P
j, cut is the load of load point excision; 2nd is switch motion total degree; 3rd is voltage out-of-limit penalty term; 4th is the out-of-limit penalty term of power; 5th is power supply reliability reduction number of users;
In above formula:
Wherein, V
jfor jth point voltage amplitude, V
j, maxand V
j, minbe respectively jth point voltage amplitude bound, S
jfor the current applied power of jth bar circuit, S
j, maxfor its power upper limit.λ
p, λ
n, λ
u, λ
s, λ
ilbe respectively every weight coefficient in objective function, value is relevant with the scale of every importance in the target and whole network; Be constrained to topological structure, the constraint of excision load, load controllability and trend accordingly.
And described power distribution network turns to be set up according to following factor for mathematical model of load: with or without guarantor electric task, Operating Complexity, dual power supply number of users, whether can transship, can cyclization factor.
And described radar map comprises protects electric task radar map and load peak radar map.
Advantage of the present invention and good effect are:
1, energy management system (EMS), distribution management system (DMS) and distribution dispatching supplementary decision system terminal are combined by dispatching communication network by this method, power distribution network is adopted to turn the core algorithm supplying load, realize the real-time online management of power distribution network, efficiently solve existing grid switching operation with the problem such as yardman's experience, efficiency is lower, improve stability and the reliability of electrical network, reduce customer outage hours.
2, the core algorithm that the power distribution network that this method adopts turns for load is regarded as a constrained Multiobjective Optimization Problem, consider with or without protecting electric task, Operating Complexity (operating switch least number of times), dual power supply number of users, whether can transship (whether branch current can be out-of-limit), can the problem of cyclization (whether busbar voltage can be out-of-limit) five key elements, and according to different situations, different weight coefficients is arranged to each key element.Such as, when having a major event, when more consideration load importance, load peak, whether more considerations can transship.According to the real-time information of power distribution network current state and line related, utilize self-adaptive threshold segmentation this optimization problem is solved, for yardman provides aid decision making foundation, formulate Optimum Operation scheme.
3, the present invention sends out and adopts the radar map in quality management system to represent five dimensions, intuitively can show the result of decision particularly.
4, the line alignment that the present invention adopts applied geography infosystem (GIS) to realize in figure conforms to actual, and the site information of each Switching Station on cue circuit, handled easily personnel reach the spot fast, greatly improves the efficiency of grid switching operation.
Accompanying drawing explanation
Fig. 1 be the present invention adopt the connection layout of system;
Fig. 2 is the processing flow chart of the self-adaptive threshold segmentation with correction of infeasible solution ability;
Fig. 3 protects electric task radar map having of distribution dispatching supplementary decision system terminal generation;
Fig. 4 is the load peak radar map generated in distribution dispatching supplementary decision system terminal.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further described.
A kind of distribution scheduling aid decision method based on various dimensions, be realize in system as shown in Figure 1, this system comprises energy management system (EMS), distribution management system (DMS) (comprising power distribution network graphics management, Geographic Information System and load transfer plan computing etc.) and multiple stage distribution dispatching supplementary decision system terminal.Energy management system (EMS), distribution management system (DMS) and multiple stage distribution dispatching supplementary decision system terminal are linked together by dispatching communication network.Wherein, energy management system (EMS) as the source of system real time data, acquisition and processing Real-time Electrical Distribution Network Data; Distribution management system (DMS) is the core of native system, inside comprises the functional modules such as power distribution network graphics management, Geographic Information System (GIS) and load transfer plan computing, it not only will manage the basic account data of Distribution Network Equipment, and by obtaining with the interface of energy management system (EMS) real time data that power distribution network runs, be optimized decision analysis, finally obtain optimum grid switching operation scheme; Distribution dispatching supplementary decision system terminal realizes, to the real-time monitoring of distribution and control, screen being provided with the contents such as graphical interfaces, operation interface, feedback interface and alarm interface.
Based on a distribution scheduling aid decision method for various dimensions, comprise the following steps:
Step 1: energy management system, distribution management system and distribution dispatching supplementary decision system terminal are linked together by dispatching communication network, as shown in Figure 1.
Step 2: energy management system (EMS) is to distribution real time monitoring and carry out data acquisition, obtains current power distribution Running State and circuit real time data information, for grid switching operation aid decision making provides effective Data Source.
Step 3: distribution management system adopts self-adaptive threshold segmentation to process power distribution network running status and track data, sets up power distribution network and turns for mathematical model of load for turning for carry calculation.
In this step, distribution management system adopts self-adaptive threshold segmentation to process power distribution network running status and track data.Its concrete processing procedure is:
(1) failure message is determined.First mark off target according to the initial information of network and failure message to turn for region, and search for available interconnection switch.
(2) generating reference colony and initial population.Stochastic generation reference group and initial population, and the adaptive value of computing reference individual in population, as reference target.Initial population is as the first generation population of evolving.In the process that reference group and initial population generate, using basic tree method to judge, whether the topological constraints of each individuality meet, if do not met, regenerate, until reach set population scale.
(3) self-adaptation immunoevolution process.After reference group and initial population generate, carry out the evolution of population according to operations such as selection, expansion, sudden changes, for newly-generated individuality, whether this individuality is feasible solution to use basic tree method to judge, if do not meet topological constraints, then correction of infeasible solution method is used to be feasible solution to its reparation.Before each evolution, parameter each in algorithm is changed according to Evolution of Population result in previous generation.
Self-adaptive threshold segmentation upgrades selection rate, expansion radius etc. according to the antibody mean distance in current population.Suppose that kth is for comprising m antibody v in antibody population Bk
i(i=1,2 ..., m), between antibody, mean distance is:
Various degree of antibody population is defined as:
In formula: d
maxfor given constant.
Selection rate (the α in kth generation
(k)), expansion radius (r
(k)) and sudden change radius (R
(k)) be respectively:
α
(k)=α
0+η
αD
(k)
r
(k)=r
0+η
r(1-D
(k))
R
(k)=R
0+η
R(1-D
(k))
In formula: α
0, r
0and R
0be respectively the minimum value of each parameter; η
α, η
rand η
rrepresent the setting range of relevant parameter respectively.
In antibody population, mean distance is less, and similarity is higher, and various degree is lower, and now selection rate reduces, and expansion radius and sudden change radius increase; Vice versa.Self-adaptive threshold segmentation can according to various degree adjustment parameter of current population to keep the diversity of population.
Due in immunoevolution process, a large amount of infeasible solutions can be produced.If directly give up these solutions, also just give up to fall some special gene comprised in these solutions, thus decreased the diversity of gene in model, thus also just reduced evolutionary rate.If repair this partial solution, make it to become feasible solution, then can accelerated evolutionary process, simultaneously can the diversity of maintainer gene.The present invention adopts the self-adaptive threshold segmentation with correction of infeasible solution ability, and as shown in Figure 2, its treatment scheme is as follows: separate P for one for stochastic generation, if be infeasible solution, becomes feasible solution by repairing; Construct one with reference to population P
re, each individuality in this population is feasible solution; From P
remiddle random selecting one separates r ∈ P
re, then stochastic generation one is from the random number a between 0 to 1, produces the series of points zi be positioned on p and r line segment according to zi=ap+ (1-a) r, until obtain a zi to meet constraint; Now, if the adaptive value of zi is greater than the adaptive value of r, then zi is replaced r, as P
rein one new for individual, thus p is repaired as feasible solution.
(4) terminate to evolve, Output rusults.When finishing iteration process after Evolution of Population to the algebraically set, export after the decoding of the individuality of adaptive value optimum, as final recovery scheme.
This method will turn regards a constrained Multiobjective Optimization Problem as load operation, consider with or without protecting electric task, Operating Complexity (operating switch least number of times), dual power supply number of users, whether can transship (whether branch current can be out-of-limit), can the factor of five aspects such as cyclization (whether busbar voltage can be out-of-limit), set up following power distribution network and turn for mathematical model of load:
In above formula, to gain merit resection sum for each load in dead electricity district for the 1st, d
jfor the weight coefficient of a jth load, depend on the kind of load, P
j, cut is the load of load point excision; 2nd is switch motion total degree; 3rd is voltage out-of-limit penalty term; 4th is the out-of-limit penalty term of power; 5th is power supply reliability reduction number of users.
Wherein:
In formula, V
jfor jth point voltage amplitude, V
j, maxand V
j, minbe respectively jth point voltage amplitude bound, S
jfor the current applied power of jth bar circuit, S
j, maxfor its power upper limit.λ
p, λ
n, λ
u, λ
s, λ
ilbe respectively every weight coefficient in objective function, value is relevant with the scale of every importance in the target and whole network.Be constrained to topological structure, the constraint of excision load, load controllability and trend accordingly.
Step 4: when needs carry out grid switching operation, yardman files an application to distribution management system in distribution dispatching supplementary decision system terminal, distribution management system use power distribution network turns and carries out analytical calculation for mathematical model of load, and in distribution dispatching supplementary decision system terminal, generate the radar map with five dimensions, Fig. 3 and Fig. 4 has provided respectively and has protected electric task radar map and load peak radar map, thus provide aid decision making foundation for yardman, be convenient to formulate Optimum Operation scheme, finally carry out grid switching operation by yardman in terminal or order field staff.
It is emphasized that; embodiment of the present invention is illustrative; instead of it is determinate; therefore the present invention includes the embodiment be not limited to described in embodiment; every other embodiments drawn by those skilled in the art's technical scheme according to the present invention, belong to the scope of protection of the invention equally.
Claims (5)
1., based on a distribution scheduling aid decision method for various dimensions, it is characterized in that: comprise the following steps:
Step 1: energy management system, distribution management system and distribution dispatching supplementary decision system terminal are linked together by dispatching communication network;
Step 2: energy management system is to distribution real time monitoring and carry out data acquisition, obtains current power distribution Running State and circuit real time data information;
Step 3: distribution management system adopts self-adaptive threshold segmentation to process power distribution network running status and track data, sets up power distribution network and turns the mathematical model supplying load, for turning for carry calculation;
Step 4: when needs carry out grid switching operation, yardman files an application to distribution management system in distribution dispatching supplementary decision system terminal, distribution management system use power distribution network turns and carries out analytical calculation for mathematical model of load, and in distribution dispatching supplementary decision system terminal, generate the radar map with five dimensions, for yardman provides aid decision making foundation;
The mathematical model that described step 3 power distribution network turns for load is:
In above formula, to gain merit resection sum for each load in dead electricity district for the 1st, d
jfor the weight coefficient of a jth load, depend on the kind of load, P
j, cutfor the load of load point excision; 2nd is switch motion total degree; 3rd is voltage out-of-limit penalty term; 4th is the out-of-limit penalty term of power; 5th is power supply reliability reduction number of users;
In above formula:
Wherein, V
jfor jth point voltage amplitude, V
j, maxand V
j, minbe respectively jth point voltage amplitude bound, S
jfor the current applied power of jth bar circuit, S
j, maxfor its power upper limit; λ
p, λ
n, λ
u, λ
s, λ
ilbe respectively every weight coefficient in objective function, value is relevant with the scale of every importance in the target and whole network; Be constrained to topological structure, the constraint of excision load, load controllability and trend accordingly.
2. the distribution scheduling aid decision method based on various dimensions according to claim 1, is characterized in that: described step 3 adopts self-adaptive threshold segmentation to comprise the following steps the detailed process that power distribution network running status and track data process:
(1) mark off target according to the initial information of network and failure message to turn for region, and search for available interconnection switch, determine failure message;
(2) stochastic generation reference group and initial population, and the adaptive value of computing reference individual in population, as reference target;
(3) according to the evolution selected, expand, mutation operation carries out population, for newly-generated individuality, whether this individuality is feasible solution to use basic tree method to judge, if do not meet topological constraints, then uses correction of infeasible solution method to be feasible solution to its reparation;
(4), when finishing iteration process after Evolution of Population to the algebraically set, export after the decoding of the individuality of adaptive value optimum, as final recovery scheme.
3. the distribution scheduling aid decision method based on various dimensions according to claim 2, it is characterized in that: the treatment scheme of described correction of infeasible solution method is: separate P for one for stochastic generation, if be infeasible solution, become feasible solution by repairing; Construct one with reference to population P
re, each individuality in this population is feasible solution; From P
remiddle random selecting one separates r ∈ P
re, then stochastic generation one is from the random number a between 0 to 1, produces the series of points zi be positioned on p and r line segment according to zi=ap+ (1-a) r, until obtain a zi to meet constraint; Now, if the adaptive value of zi is greater than the adaptive value of r, then zi is replaced r, as P
rein one new for individual, thus p is repaired as feasible solution.
4. the distribution scheduling aid decision method based on various dimensions according to claim 1, is characterized in that: the mathematical model that described power distribution network turns for load is set up according to following factor: with or without guarantor electric task, Operating Complexity, dual power supply number of users, whether can transship, can cyclization factor.
5. the distribution scheduling aid decision method based on various dimensions according to claim 1, is characterized in that: described radar map comprises protects electric task radar map and load peak radar map.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310271161.XA CN103390249B (en) | 2013-07-01 | 2013-07-01 | Based on the distribution scheduling aid decision method of various dimensions |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310271161.XA CN103390249B (en) | 2013-07-01 | 2013-07-01 | Based on the distribution scheduling aid decision method of various dimensions |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103390249A CN103390249A (en) | 2013-11-13 |
| CN103390249B true CN103390249B (en) | 2016-03-30 |
Family
ID=49534512
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310271161.XA Active CN103390249B (en) | 2013-07-01 | 2013-07-01 | Based on the distribution scheduling aid decision method of various dimensions |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103390249B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103873328A (en) * | 2014-03-04 | 2014-06-18 | 赵孔燕 | Data transmission method between EMS and DMS |
| CN105321014A (en) * | 2014-07-01 | 2016-02-10 | 国家电网公司 | Distribution network resource and information first-aid repair optimization scheduling method |
| CN110852627B (en) * | 2019-11-13 | 2022-06-24 | 国电南瑞科技股份有限公司 | Decision method and device for post-disaster first-aid repair of power distribution network |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179195A (en) * | 2007-11-15 | 2008-05-14 | 上海交通大学 | Power distribution network planning scheme assistant decision system |
| CN101887547A (en) * | 2010-06-30 | 2010-11-17 | 广西电网公司电力科学研究院 | Assistant decision system for condition-based maintenance and risk evaluation of power transmission and transformation equipment |
| CN101958536A (en) * | 2010-09-20 | 2011-01-26 | 中国电力科学研究院 | Distribution network failure isolation and quick power service restoration decision support system |
| CN102545212A (en) * | 2012-01-10 | 2012-07-04 | 中国电力科学研究院 | Electrical energy quality centralized monitoring and auxiliary management decision support system |
-
2013
- 2013-07-01 CN CN201310271161.XA patent/CN103390249B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101179195A (en) * | 2007-11-15 | 2008-05-14 | 上海交通大学 | Power distribution network planning scheme assistant decision system |
| CN101887547A (en) * | 2010-06-30 | 2010-11-17 | 广西电网公司电力科学研究院 | Assistant decision system for condition-based maintenance and risk evaluation of power transmission and transformation equipment |
| CN101958536A (en) * | 2010-09-20 | 2011-01-26 | 中国电力科学研究院 | Distribution network failure isolation and quick power service restoration decision support system |
| CN102545212A (en) * | 2012-01-10 | 2012-07-04 | 中国电力科学研究院 | Electrical energy quality centralized monitoring and auxiliary management decision support system |
Non-Patent Citations (2)
| Title |
|---|
| 基于自适应免疫算法和预测-校正内点法的无功优化;林济铿,李鸿路,仝新宇;《天津大学学报》;20080229;第41卷(第2期);168-174页 * |
| 配电网规划计算机辅助决策系统;张二飞，冯林桥，刘金玲，李涵，杨艳玲;《电力系统保护与控制》;20080616;第36卷(第12期);56-59页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103390249A (en) | 2013-11-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102983629B (en) | Auxiliary decision-making method for on-line power system restoration | |
| CN103532140B (en) | A kind of method and system containing service restoration after the distribution network failure of distributed power source | |
| CN109948868A (en) | High permeability distribution type renewable energy power generation cluster Method for optimized planning | |
| CN108122068A (en) | A kind of power distribution network risk-averse retailer method and system | |
| CN104102956B (en) | Distribution network expansion planning method based on strategy adaption differential evolution | |
| CN104200263B (en) | Power distribution network route planning method based on tabu differential evolution and GIS (Geographic Information System) | |
| CN106503839A (en) | A kind of marine wind electric field annular current collection network hierarchy planing method | |
| CN109146124B (en) | Power distribution terminal transformation decision method based on time-varying failure rate | |
| CN104037765B (en) | The method of active power distribution network service restoration scheme is chosen based on improved adaptive GA-IAGA | |
| CN104751246A (en) | Active distribution network planning method based on stochastic chance constraint | |
| Abushamah et al. | A novel approach for distributed generation expansion planning considering its added value compared with centralized generation expansion | |
| CN105512472A (en) | Large-scale wind power base power influx system topology composition layered optimization design and optimization design method thereof | |
| CN105576660A (en) | Region power distribution network on-line simulation analysis device and system | |
| CN104899689B (en) | Based on the distribution network failure restoration methods that DBCC optimized algorithms and entropy weight are theoretical | |
| CN103390249B (en) | Based on the distribution scheduling aid decision method of various dimensions | |
| CN114744616A (en) | Power recovery auxiliary decision-making method for power distribution network | |
| Chai et al. | Application of Digital Twin and Hologram Technology to Achieve Distribution Network Reliability Forecast | |
| CN111222649A (en) | Self-healing capacity improvement planning method for power distribution network | |
| Lu et al. | Clean generation mix transition: Large-scale displacement of fossil fuel-fired units to cut emissions | |
| Zemite et al. | Genetic algorithm for optimization of power switch allocation in distribution network | |
| CN109002938B (en) | Double-layer planning method for alternating current-direct current hybrid power distribution network considering N-1 safety criterion | |
| CN113852084B (en) | Multi-stage toughness improvement method for power distribution network considering intelligent soft switch optimization configuration | |
| CN111724025A (en) | High-voltage distribution network frame planning method based on power supply unit optimized division | |
| CN111369388A (en) | Method and system for evaluating anti-vulnerability of urban power grid | |
| CN106651113A (en) | Dispatcher operation risk evaluation method based on advanced N-1 analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |